Janne Heilala, Antti Salminen, Wallace Moreira Bessa, Jussi Kantola
{"title":"优化智能工厂:数据驱动法","authors":"Janne Heilala, Antti Salminen, Wallace Moreira Bessa, Jussi Kantola","doi":"10.34257/gjregvol23is3pg15","DOIUrl":null,"url":null,"abstract":"Since the first industrial revolution, the leading role of emerging technologies has been highlighted in modernizing the industry and developing the workforce. This study explores the impact of Industry 4.0 digital technologies on manufacturing competitiveness, focusing on Finnish SMEs within the EU with a sample (n = 123). It utilizes extensive 2022 European Manufacturing Survey (EMS22) data. Advanced statistical techniques reveal complex connections between automation, competitive edge on services, and innovation models, among other factors. Robust statistical methods, including component and reliability analyses, reinforced the findings. The conclusion offers critical insights and identifies areas for further research in combining innovative manufacturing practices with technology education.","PeriodicalId":342934,"journal":{"name":"Global Journal of Researches in Engineering","volume":"93 4","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimizing Smart Factories: A Data-Driven Approach\",\"authors\":\"Janne Heilala, Antti Salminen, Wallace Moreira Bessa, Jussi Kantola\",\"doi\":\"10.34257/gjregvol23is3pg15\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Since the first industrial revolution, the leading role of emerging technologies has been highlighted in modernizing the industry and developing the workforce. This study explores the impact of Industry 4.0 digital technologies on manufacturing competitiveness, focusing on Finnish SMEs within the EU with a sample (n = 123). It utilizes extensive 2022 European Manufacturing Survey (EMS22) data. Advanced statistical techniques reveal complex connections between automation, competitive edge on services, and innovation models, among other factors. Robust statistical methods, including component and reliability analyses, reinforced the findings. The conclusion offers critical insights and identifies areas for further research in combining innovative manufacturing practices with technology education.\",\"PeriodicalId\":342934,\"journal\":{\"name\":\"Global Journal of Researches in Engineering\",\"volume\":\"93 4\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Global Journal of Researches in Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.34257/gjregvol23is3pg15\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Global Journal of Researches in Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.34257/gjregvol23is3pg15","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Optimizing Smart Factories: A Data-Driven Approach
Since the first industrial revolution, the leading role of emerging technologies has been highlighted in modernizing the industry and developing the workforce. This study explores the impact of Industry 4.0 digital technologies on manufacturing competitiveness, focusing on Finnish SMEs within the EU with a sample (n = 123). It utilizes extensive 2022 European Manufacturing Survey (EMS22) data. Advanced statistical techniques reveal complex connections between automation, competitive edge on services, and innovation models, among other factors. Robust statistical methods, including component and reliability analyses, reinforced the findings. The conclusion offers critical insights and identifies areas for further research in combining innovative manufacturing practices with technology education.